Major Big Data Challenges in Most Industries and Innovative Solutions
Shanmugasundaram Palanimalai1, R. Velusamy2, P. Vijaykumar3

1Dr. Shanmugasundaram Palanimalai, Project Manager Information Technology, Bangalore (Karnataka), India.

2R. Velusamy, Research Scholar, Bharathiar University Arts & Science College, Mudakkuruchi, Erode (Tamil Nadu), India.

3Dr. P. Vijaykumar, AP, Bharathiar University Arts & Science College, Mudakkuruchi, Erode (Tamil Nadu), India.

Manuscript received on 04 December 2019 | Revised Manuscript received on 16 December 2019 | Manuscript Published on 30 December 2019 | PP: 424-428 | Volume-9 Issue-2S2 December 2019 | Retrieval Number: B11431292S219/2019©BEIESP | DOI: 10.35940/ijitee.B1143.1292S219

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The term “Big data” refers to “the high volume of data sets that are relatively complex in nature and having challenges in processing and analyzing the data using conventional database management tools”. In the digital universe, the data volume and variety that, we deal today have grown-up massively from different sources such as Business Informatics, Social-Media Networks, Images from High Definition TV, data from Mobile Networks, Banking data from ATM Machines, Genomics and GPS Trails, Telemetry from automobiles, Meteorology, Financial market data etc. Data Scientists confirm that 80% of the data that we have gathered today are in unstructured format, i.e. in the form of images, pixel data, Videos, geo-spatial data, PDF files etc. Because of the massive growth of data and its different formats, organizations are having multiple challenges in capturing, storing, mining, analyzing, and visualizing the Big data. This paper aims to exemplify the key challenges faced by most organizations and the significance of implementing the emerging Big data techniques for effective extraction of business intelligence to make better and faster decisions.

Keywords: Big Data, Hadoop, HDFS, MapReduce, No-SQL.
Scope of the Article: Big Data Security